In [1]:
import pandas as pd
import matplotlib.pyplot as plt
from pandas import ExcelWriter
import os
import numpy as np
import random
plt.style.use("seaborn")

Healthy Samples

In [22]:
Parameters = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Modelling/HealthySamples.xlsx")
In [23]:
Parameters
Out[23]:
Unnamed: 0 Unnamed: 0.1 Patient Sensor1_max Sensor2_max Sensor3_min Latency UES_start UES_end UES_Duration Sample status
0 0 0 Control 1.txt 192.279698 113.474479 -20.601968 -0.028 1552.752 1553.392 0.640 Perfect
1 1 1 Control 1.txt 167.821012 98.336004 -11.776150 -0.028 1782.184 1782.896 0.712 Perfect
2 2 2 Control 1.txt 171.739528 249.844358 -24.181735 -0.036 611.556 612.284 0.728 Perfect
3 3 5 Control 1.txt 200.377661 107.578393 -16.358434 -0.092 2333.764 2334.412 0.648 Perfect
4 4 6 Control 1.txt 193.675898 105.770199 -25.335317 -0.172 1697.164 1697.784 0.620 Perfect
... ... ... ... ... ... ... ... ... ... ... ...
195 195 39 P24_F_27.txt 81.341268 161.707485 -13.554589 0.120 198.240 199.008 0.768 Perfect
196 196 49 P24_F_27.txt 82.632181 211.714351 -9.086748 0.276 192.688 193.624 0.936 Perfect
197 197 51 P24_F_27.txt 110.199130 167.292287 -21.098650 0.412 77.764 78.884 1.120 Perfect
198 198 56 P24_F_27.txt 83.648432 235.317006 -13.838407 0.120 195.080 195.940 0.860 Perfect
199 199 60 P24_F_27.txt 89.141680 184.495308 -14.048981 0.196 711.212 712.000 0.788 Perfect

200 rows × 11 columns

In [24]:
count = 1
for i in range(0, len(Parameters)):
    if Parameters.loc[i][10] == "Perfect":
        data = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Healthy/Samples/" + Parameters.loc[i][2][:-4] + "/" + Parameters.loc[i][2][:-4] + "_" + str(Parameters.loc[i][1]) + ".xlsx")
        data.Time = pd.to_numeric(data.Time, errors='coerce')
        data.Sensor1 = pd.to_numeric(data.Sensor1, errors='coerce')
        data.Sensor2 = pd.to_numeric(data.Sensor2, errors='coerce')
        data.Sensor3 = pd.to_numeric(data.Sensor3, errors='coerce')
        data.index = data.Time
        ax = data.plot.line(x='Time', y=["Sensor1", "Sensor2", "Sensor3"],figsize = (15, 8 ))
        b = data[data["Sensor1"] == Parameters.loc[i][3]]
        c = data[data["Sensor2"] == Parameters.loc[i][4]]
        d = data[data["Sensor3"] == Parameters.loc[i][5]]
        fro = data[data["Sensor3"] == data.loc[Parameters.loc[i][7]][4]]
        to = data[data["Sensor3"] == data.loc[Parameters.loc[i][8]][4]]
        b.plot.scatter(x="Time", y="Sensor1", ax=ax,color="r", marker="o",s=50)
        c.plot.scatter(x="Time", y="Sensor2", ax=ax,color="r", marker="o",s=50)
        d.plot.scatter(x="Time", y="Sensor3", ax=ax,color="r", marker="o",s=50)
        fro.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
        to.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
        print("Sample: ",count)
        plt.show()
        count = count + 1
    else:
        pass
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Unhealthy Samples

In [19]:
Parameters = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Modelling/UnHealthySamples.xlsx")
In [20]:
Parameters
Out[20]:
Unnamed: 0 Unnamed: 0.1 Patient Sensor1_max Sensor2_max Sensor3_min Latency UES_start UES_end UES_Duration Sample status
0 0 0 HD011C.txt 254.3694 113.88430 -9.446444 0.194 22.749 23.334 0.585 Perfect
1 1 1 HD011C.txt 183.8655 128.26630 -14.236160 0.216 6.871 7.552 0.681 Perfect
2 2 2 HD011C.txt 228.7961 141.95400 -8.533228 0.214 7.882 8.499 0.617 Perfect
3 3 3 HD011C.txt 240.5188 80.61724 -7.899569 0.188 13.298 13.891 0.593 Perfect
4 4 4 HD011C.txt 243.0201 122.63250 -18.783600 0.141 18.029 18.597 0.568 Perfect
... ... ... ... ... ... ... ... ... ... ... ...
197 197 477 HD11B.txt 209.1134 79.38563 -12.359970 0.192 61.255 61.856 0.601 Perfect
198 198 478 HD11B.txt 257.1539 64.76777 -12.154600 0.031 105.364 105.844 0.480 Correction
199 199 479 HD11B.txt 298.4223 28.70255 -16.952760 -0.132 37.756 38.331 0.575 Correction
200 200 480 HD11B.txt 306.7658 38.74133 -9.447460 0.140 74.398 74.974 0.576 Correction
201 201 481 HD11B.txt 309.8712 59.28852 -9.540810 0.110 10.308 10.866 0.558 Perfect

202 rows × 11 columns

In [21]:
count = 1
for i in range(0, len(Parameters)):
    if Parameters.loc[i][10] == "Perfect":
        data = pd.read_excel("D:/DATA SCIENCE/INTERNSHIP PROJECT/Unhealthy/Samples/" + Parameters.loc[i][2][:-4] + "/" + Parameters.loc[i][2][:-4] + "_" + str(Parameters.loc[i][1]) + ".xlsx")
        data.Time = pd.to_numeric(data.Time, errors='coerce')
        data.Sensor1 = pd.to_numeric(data.Sensor1, errors='coerce')
        data.Sensor2 = pd.to_numeric(data.Sensor2, errors='coerce')
        data.Sensor3 = pd.to_numeric(data.Sensor3, errors='coerce')
        data.index = data.Time
        ax = data.plot.line(x='Time', y=["Sensor1", "Sensor2", "Sensor3"],figsize = (15, 8 ))
        b = data[data["Sensor1"] == Parameters.loc[i][3]]
        c = data[data["Sensor2"] == Parameters.loc[i][4]]
        d = data[data["Sensor3"] == Parameters.loc[i][5]]
        fro = data[data["Sensor3"] == data.loc[Parameters.loc[i][7]][4]]
        to = data[data["Sensor3"] == data.loc[Parameters.loc[i][8]][4]]
        b.plot.scatter(x="Time", y="Sensor1", ax=ax,color="r", marker="o",s=50)
        c.plot.scatter(x="Time", y="Sensor2", ax=ax,color="r", marker="o",s=50)
        d.plot.scatter(x="Time", y="Sensor3", ax=ax,color="r", marker="o",s=50)
        fro.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
        to.plot.scatter(x="Time", y="Sensor3", ax=ax,color="b", marker="o",s=50)
        print("Sample: ", count)
        plt.show()
        count = count + 1
    else:
        pass
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